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Journal of Career Development
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Large Scale Survey Data in Career Development Research

Matthew A. Diemer

Michigan State University, diemerm{at}msu.edu

Large scale survey datasets have been underutilized but offer numerous advantages for career development scholars, as they contain numerous career development constructs with large and diverse samples that are followed longitudinally. Constructs such as work salience, vocational expectations, educational expectations, work satisfaction, and occupational attainment are readily available. With a few notable exceptions, studies of these datasets are infrequent in the career development literature. This article reviews the strengths and weaknesses of these datasets for career development research, the technical aspects of complex sample design, and software options for analyses. Career development scholars must understand complex sample design and analysis strategies to avoid drawing inappropriate conclusions from analyses of large scale survey data. Through illuminating the potential of large scale survey datasets, providing a more user-friendly introduction to the features of complex sample design, and reviewing data analysis options, this article aims to increase the utilization of large scale survey datasets by career development scholars.

Key Words: career development • complex sample data • large scale surveys • secondary analysis

Journal of Career Development, Vol. 35, No. 1, 42-59 (2008)
DOI: 10.1177/0894845308317935
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 Journal of Career DevelopmentHome page
L. Y. Flores
Introduction to Special Issue: Innovative Methodological Advances in Career Development Research and Practice
Journal of Career Development, September 1, 2008; 35(1): 3 - 4.
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